class_docstr: Given wrapped example, e.g. A fun movie ! it is <mask> and <mask> .
  The input tokens is:  A fun movie ! it is <s_0> and <s_1> . <eod>
  The decoder tokens is: <s> <s_0> <s_1> <eod>
  The expected output is: <s_0> good <s_1> interesting </s>
  Another solution is add verbalizer label words into the labels, thus generating
  'interesting' given 'good'. However, it is not implemented in this version.
code: def mask_token(self, i):
      return self.tokenizer.additional_special_tokens[i]
  
imports: from json import decoder
  from transformers.tokenization_utils import PreTrainedTokenizer
  from openprompt.plms.utils import TokenizerWrapper
  from typing import List, Dict, Optional
  from collections import defaultdict
  from openprompt.utils.logging import logger
label_desc: Use image node_id 2 for calling the CPM2TokenizerWrapper obj's underlying member method code with example usage: obj.mask_token(i) and returns: self